Instructions to use LRJ1981/Rito_Version1.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LRJ1981/Rito_Version1.2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LRJ1981/Rito_Version1.2") model = AutoModelForSeq2SeqLM.from_pretrained("LRJ1981/Rito_Version1.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LRJ1981/Rito_Version1.2: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/LRJ1981/Rito_Version1.2/resolve/main/training_args.bin
- Command line
-
hf download hf://LRJ1981/Rito_Version1.2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LRJ1981/Rito_Version1.2/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- d66d19176c2d5c7d4309a0783e2cf795c230042838442a98233c020cfa892248
- Size of remote file:
- 5.18 kB
- SHA256:
- 62a6bb28bb360013bcfdc07feeb3365525520a2ae613255247c1fd2e2eb4289c
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